TYK2 DMS manuscript - Fig 1 supplement -

Robert Warneford-Thomson

• 1 I. SETUP
  • 1.0.1 Packages
  • 1.0.2 Variables
• 2 Functions
  • 2.1 compute_difference
  • 2.2 theme_pub
• 3 Load and format data
• 4 Figures
  • 4.1 Fig S1B - Flow + IFNa-1,10,100 heatmaps
  • 4.2 Fig S1C - Barplots with LoF/GoF counts
  • 4.3 Fig S1D - stop effect density plots
  • 4.4 Fig S1F - Fiducial variant forest plot
  • 4.5 Fig S1E, S1G - Beeswarm with ClinVar, ESM, AlphaMissense etc
  • 4.6 Merged Figure S1

I. SETUP

Packages

Code

pacman::p_load(
  colorspace,
  ggbeeswarm,
  ggnewscale,
  ggh4x,
  ggpubr,
  ggsci,
  magrittr,
  paletteer,
  patchwork,
  scico,
  tidyverse
)

Variables

Code

knitr::opts_chunk$set(
  echo = FALSE,
  fig.path = "./fig-1/",
  fig.dpi=600,
  warning = FALSE,
  message = FALSE,
  dev = c("png", "pdf")
)
setwd("~/Analyses/bms-dms/paper")

cbPalette <- c("#DC5E65", "darkgrey", "#0072B2", "#56B4E9", "#E69F00", "#009E73", "#F0E442", "pink", "#CC79A7", "lightgrey", "grey")

aa_order <- c(
  "*", "P", "G", "A", "M", "V", "L", "I", "T", "S",
  "C", "Q", "N", "Y", "W", "F", "E", "D", "K", "H", "R"
)

source("../../dms/src/model/dms-analysis-utils.R")

Functions

compute_difference

theme_pub

Load and format data

After discussing with Conor, will use 1 and 10 U/mL IFNa data from run3, and 100 U/mL IFNa from run7

Figures

Fig S1B - Flow + IFNa-1,10,100 heatmaps

Fig S1C - Barplots with LoF/GoF counts

I’m going to just use a 1% FDR to determine GoF and LoF variants with no minimum log2fold or midpoint shift threshold

Fig S1D - stop effect density plots

Fig S1F - Fiducial variant forest plot

Fig S1E, S1G - Beeswarm with ClinVar, ESM, AlphaMissense etc

Merged Figure S1

Figure 1